Dynamic Incentive Mechanism Design for COVID-19 Social Distancing
Keywords:Incentive Mechanism, Crowdsourcing, Crowd Counting
AbstractAs countries enter the endemic phase of COVID-19, people's risk of exposure to the virus is greater than ever. There is a need to make more informed decisions in our daily lives on avoiding crowded places. Crowd monitoring systems typically require costly infrastructure. We propose a crowd-sourced crowd monitoring platform which leverages user inputs to generate crowd counts and forecast location crowdedness. A key challenge for crowd-sourcing is a lack of incentive for users to contribute. We propose a Reinforcement Learning based dynamic incentive mechanism to optimally allocate rewards to encourage user participation.
How to Cite
Ho, X. R. Z., Lim, W. Y. B., Jiang, H., Ng, J. S., Yu, H., Xiong, Z., Niyato, D., & Miao, C. (2022). Dynamic Incentive Mechanism Design for COVID-19 Social Distancing. Proceedings of the AAAI Conference on Artificial Intelligence, 36(11), 13173-13175. https://doi.org/10.1609/aaai.v36i11.21718
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